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MULTI-VIEW LEARNING

Multi-View Learning is a machine learning framework where data are represented by multiple distinct feature groups, and each feature group is referred to as a particular view.

Source: Dissimilarity-based representation for radiomics applications

Papers

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Showing 151–200 of 256 papers

TitleStatusHype
Improving Sentence Representations with Multi-view Frameworks—0
Imputation of missing values in multi-view data—0
Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization—0
Incorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering—0
Information Theory-Guided Heuristic Progressive Multi-View Coding—0
Information Theory-Guided Heuristic Progressive Multi-View Coding—0
InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction—0
Joint Adaptive Neighbours and Metric Learning for Multi-view Subspace Clustering—0
Joint Embedding Learning and Low-Rank Approximation: A Framework for Incomplete Multi-view Learning—0
Jointly Deep Multi-View Learning for Clustering Analysis—0
Latent Heterogeneous Graph Network for Incomplete Multi-View Learning—0
Layer-Wise Multi-View Learning for Neural Machine Translation—0
Learnable Graph Convolutional Network and Feature Fusion for Multi-view Learning—0
Learning Common Representation from RGB and Depth Images—0
Reliable Representations Learning for Incomplete Multi-View Partial Multi-Label Classification—0
Locality Relationship Constrained Multi-view Clustering Framework—0
Mammo-Clustering:A Weakly Supervised Multi-view Global-Local Context Clustering Network for Detection and Classification in Mammography—0
Marine Animal Classification with Correntropy Loss Based Multi-view Learning—0
Masked Two-channel Decoupling Framework for Incomplete Multi-view Weak Multi-label Learning—0
Few-shot Partial Multi-view Learning—0
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding—0
MERIT: Multi-view Evidential learning for Reliable and Interpretable liver fibrosis sTaging—0
MetaViewer: Towards A Unified Multi-View Representation—0
MHCN: A Hyperbolic Neural Network Model for Multi-view Hierarchical Clustering—0
ML-LocNet: Improving Object Localization with Multi-view Learning Network—0
Modal Regression based Structured Low-rank Matrix Recovery for Multi-view Learning—0
MultiEarth 2023 Deforestation Challenge -- Team FOREVER—0
Multimodal and Multi-view Models for Emotion Recognition—0
Multi-Participant Multi-Class Vertical Federated Learning—0
Multi-view Audio and Music Classification—0
Multi-view Bayesian optimisation in reduced dimension for engineering design—0
Multi-View Class Incremental Learning—0
Multi-view Data Classification with a Label-driven Auto-weighted Strategy—0
Multi-View Fuzzy Logic System with the Cooperation between Visible and Hidden Views—0
Multi-view graph structure learning using subspace merging on Grassmann manifold—0
Multi-View Incongruity Learning for Multimodal Sarcasm Detection—0
Multi-View Incremental Learning with Structured Hebbian Plasticity for Enhanced Fusion Efficiency—0
Multi-view Instance Attention Fusion Network for classification—0
Multi-View Intact Space Learning—0
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis—0
Multi-view learning for automatic classification of multi-wavelength auroral images—0
Multi-view learning for multivariate performance measures optimization—0
Multi-View Learning for Vision-and-Language Navigation—0
Multi-View Learning for Web Spam Detection—0
Multi-View Learning of Word Embeddings via CCA—0
Multi-view learning with privileged weighted twin support vector machine—0
Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation—0
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds—0
Multi-view metric learning for multi-instance image classification—0
Multi-View Multi-Task Modeling with Speech Foundation Models for Speech Forensic Tasks—0
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